Communication Interface Research Articles

Enhancing IoT data acquisition efficiency via FPGA-based implementation with OpenCL framework

The increasing demand for real-time data processing in Internet of Things (IoT) applications necessitates the development of efficient and flexible data acquisition systems capable of receiving and processing data from various sensor types. In conjunction with OpenCL, field-programmable gate arrays (FPGAs) have recently emerged as powerful platforms for accelerating data-intensive tasks. This study explored the implementation of an FPGA for data acquisition using OpenCL, aiming to design and implement an efficient data acquisition system tailored for IoT applications. Utilizing OpenCL for FPGA-based data acquisition offers several advantages that contribute to system efficiency, particularly in hardware interfaces between FPGA and external devices used in IoT applications. OpenCL abstracts the complexity of the FPGA hardware interface to external DDR memory for storing temporary data and a communication interface to the host CPU for transferring the collected data and enabling remote access, enabling developers to focus on algorithm design and functionality. To enable data reading from an external analog-to-digital converter (ADC) chip for IoT applications, we developed a component module that utilizes the Avalon-streaming interface and can stream the data to the OpenCL kernel. An experiment was conducted to demonstrate the performance of our proposed design. According to the findings of the experiments, a data acquisition implementation based on an FPGA and OpenCL can simultaneously read analog signals via a multichannel ADC. The proposed design provides a foundation for designing efficient data acquisition solutions, addressing the increasing needs of FPGA-based data acquisition in various IoT environments.

Neural Network Algorithm for Training a Mobile Robot in the Task of Following a Target

The article is devoted to the research, development and implementation of an artificial neural network with reinforcement for controlling a mobile robot with a differential drive to solve the task of following a target. The authors of the study present a detailed description of the architecture of the neural network, its training using a deep deterministic gradient policy algorithm, and integration with the robot control system. A distributed neural network structure was selected for specialized generation of controls, for which the authors chose the angular and linear speed of the robot. A system of rules has been synthesized that takes into account changes in the distance between the robot and the target object and tracking of the heading angle in real time. A mathematical model of a robot with a differential drive is considered, on the basis of which a simulation program is implemented for intermediate training of a neural network, as a result of which the initial weighting coefficients are formed. Using this program, you can get by with less energy and time costs at the initial stage of the study. Experiments to test the effectiveness of the developed neural network were carried out in the Gazebo simulation environment using the ROS2 communication interface. The article describes the process of integrating a neural network with a robot control system in a simulation environment, as well as test results and analysis of the obtained data. The results of experiments are presented for three scenarios in which the initial position of the robot is the same, the remaining parameters are generated according to the rules described by the authors. The effectiveness of using such a solution for trajectory planning has been confirmed. The research contributes to the field of autonomous systems and demonstrates the potential of artificial reinforcement neural networks in robotics.

A cognitive load assessment method for fighter cockpit human-machine interface based on integrated multi-criteria decision making

The primary interface for communication between pilots and aircraft systems is the fighter cockpit Human-Machine Interface (HMI). Since reduced cognitive load ensures that pilots will operate the aircraft safely and effectively, it is critical to evaluate pilot cognitive load during HMI. A cognitive load assessment method, based on multi-criteria decision-making, is proposed to accurately quantify the relationship between the HMI and the cognitive load in the fighter’s cockpit. Firstly, based on the integrated Multi-Criteria Decision-Making (MCDM) method, the Step-wise Weight Assessment Ratio Analysis (SWARA) and MEthod based on the Removal Effects of Criteria (MEREC) methods are used to assign subjective and objective weights, respectively. Moreover, the Combined Compromise Solution (CoCoSo) method is applied to rank the scenarios to establish a cognitive load assessment model for the cockpit HMI of the fighter jet. Secondly, an evaluation standard system of fighter cockpit HMI is proposed, drawn upon multiple sets of eye-movement criteria and subjective assessment criteria. Moreover, cognitive load experiments of fighter cockpit HMI are conducted using eye-tracking technology to get the objective physiological cognitive data as well as the subjective assessment data of the subjects. Consequently, the parameter data sets of the eye-movement criteria and the subjective criteria for the evaluation of cognitive load are obtained. The proposed method is applied to analyze the cognitive load assessment of a fighter jet cockpit HMI layout. This application aims to verify the effectiveness of the assessment method in evaluating the cognitive load of the HMI layout. Through sensitivity and comparison analyses, the model was further verified to have excellent robustness and applicability for cognitive load assessment. The advantages of this method can be seen through the comparison, which is that it has higher discriminability when assessing the degree of cognitive load. At the same time, it has higher flexibility in dealing with complex and ambiguous cognitive load assessment information.

A heterogeneous ultrasound open scanner for the real-time implementation of computationally demanding imaging methods.

Ultrasound open scanners have recently boosted the development and validation of novel imaging techniques. They are usually split into hardware- or software-oriented systems, depending on whether they process the echo data using embedded FPGAs/DSPs or a GPU on a host PC. The goal of this work was to realize a high-performance heterogeneous open scanner capable of leveraging the strengths of both hardware and software-oriented systems. The elaboration power of the 256-channel ultrasound advanced open platform (ULA-OP 256) was further enhanced by embedding a compact co-processing GPU system-on-module (SoM). By carefully avoiding latencies and overheads through low-level optimization work, an efficient PCIe communication interface was established between the GPU and the processing devices onboard the ULA-OP 256. As a proof of concept of the enhanced system, the high frame rate color flow mapping technique was implemented on the GPU SoM and tested. Compared to a previous DSP-based implementation, higher real-time frame rates were achieved together with unprecedented flexibility in setting crucial parameters such as the ensemble length (EL). For example, by setting EL=64 and a continuous-time high-pass filter, the flow was investigated with high temporal and spatial resolution in the femoral vein bifurcation (frame rate = 1.1 kHz) and carotid artery bulb (4.3 kHz), highlighting the flow disturbances due to valve aperture and secondary velocity components, respectively. The results of this work promote the development of other computational-expensive processing algorithms in real-time and may inspire the next generation of ultrasound high-performance heterogeneous scanners.

Evaluation of Pedestrians' Gaze Behavior When Crossing the Road Using Eye-Tracking Technology: Implications for Autonomous Vehicle Led Communication Interface

Evaluation of Pedestrians' Gaze Behavior When Crossing the Road Using Eye-Tracking Technology: Implications for Autonomous Vehicle Led Communication Interface

Brain Function, Learning, and Role of Feedback in Complete Paralysis.

The determinants and driving forces of communication abilities in the locked-in state are poorly understood so far. Results from an experimental-clinical study on a completely paralyzed person involved in communication sessions after the implantation of a microelectrode array were retrospectively analyzed. The aim was to focus on the prerequisites and determinants for learning to control a brain-computer interface for communication in paralysis. A comparative examination of the communication results with the current literature was carried out in light of an ideomotor theory of thinking. We speculate that novel skill learning took place and that several aspects of the wording of sentences during the communication sessions reflect preserved cognitive and conscious processing. We also present some speculations on the operant learning procedure used for communication, which argues for the reformulation of the previously postulated hypothesis of the extinction of response planning and goal-directed ideas in the completely locked-in state. We highlight the importance of feedback and reinforcement in the thought-action-consequence associative chain necessary to maintain purposeful communication. Finally, we underline the necessity to consider the psychosocial context of patients and the duration of complete immobilization as determinants of the 'extinction of thinking' theory and to identify the actual barriers preventing communication in these patients.

Drivers of Knowledge Sharing in Virtual Brand Communities: Self-Determination Perspective

ABSTRACT The prevalence of virtual brand communities and the knowledge sharing occurring throughout these populations has become a staple of both business and consumer online realities. Expanding work on personal motivations, and guided by self-determination theory, this research explores autonomous and relatedness motivations that drive individual knowledge sharing within online communities. The authors argue that such knowledge sharing can be fostered by many drivers, including self-presentation factors, brand community engagement elements, user attitude toward the brand, user reputation, size of community network, and reciprocity from other community members. Analysis was conducted using data collected longitudinally from 2866 club members of Xiaomi’s online MI User Interface community in China. Results reveal that personal signature, post length, online time, login frequency, brand attitude, reputation, online social network, and reciprocity all positively affect individual knowledge sharing within the virtual brand community, while the use of picture posts may have adverse effects and impact knowledge sharing negatively.

Development of a Smart Metering System for Efficient Energy Consumption

Smart energy concepts are based on the utilization of emerging integrated microprocessors and communication technologies for monitoring energy consumption. In the utilization of electricity, energy management is a core problem, especially for cost savings to the benefit of electricity customers. In modern electricity generation, transmission and consumption, energy management has occupied the center of attention for sustainable techno-economic motives. The present-day power sector has an immense role to play in the overall economic performance of the global community, thus, requiring the application of efficient and reliable metering systems for the measurement of energy consumption. The application of a smart metering system depends on the effectiveness of the embedded smart communication interface in the utility service provider system and the energy consumers’ metering devices based on energy supply reliability and consumption security. Therefore, this study focuses on the design and development of an efficient smart energy meter using the advancements provided by the Internet of Things (IoTs). The system was tested based on the collection of real-time data and subsequently analyzed for performance evaluation through a case study of household data collection.

Who are the best contributors? Designing a multimodal science communication interface based on the ECM, TAM and the Taguchi methods

Science communication conducted through mobile devices and mobile applications is an efficient and widespread phenomenon that requires communicators and design practitioners to further develop suitable design elements and strategies for such platforms. The effective application of multimodal or multisensory design in interfaces provides users with rich experiences. However, there is a lack of guiding recommendations for user interface design in the citizen science community. This study investigated factors affecting users’ perceptions and behavioral intentions toward multimodal scientific communication interface designs and identified the optimal combinations of such factors for such designs. Through a focus group, we defined three design dimensions of a science communication interface: visual, auditory, and haptic. An online experiment involving 916 participants was then conducted and integrated the technology acceptance model, expectation–confirmation model, and Taguchi method to examine the hierarchical combinations with the greatest influence in each dimension. The results indicated that interface design combinations primarily focusing on visual elements, with auditory and haptic as secondary elements, can serve as effective tools for science communication. Moreover, layout, color tones, vibration intensity, and sound volume significantly affected users’ perceptions and behavioral intentions. As one of the few studies using the Taguchi method to explore the design of science communication interfaces, the present findings enrich the multimodal theory from the perspectives of design and communication, highlighting its value in science communication. This paper simultaneously provides insights into how to select and combine multimodal design elements in science communication interfaces, demonstrating the potential of such designs to affect a user perception, satisfaction, confirmation, and continued usage intention.

Green Computing: Crafting A Low-Energy Amba APB Bridge Solution

Abstract—The Advanced High-performance Bus (AHB), a key component of the Advanced Microcontroller Bus Architecture (AMBA) family, stands as a high-performance, low-power, and high- bandwidth communication interface within system components. Bridging to low-bandwidth peripherals, the Advanced Peripheral Bus (APB) offers a simple, non-pipelined protocol for read- and-write communication, linking a bridge/master to numerous slaves via a shared bus. The AHB to APB bridge serves a critical role in integrating diverse bus protocols, facilitating efficient communication between high-performance processing units and slower peripherals, thereby enhancing the System-on-Chip (SoC)'s overall effectiveness and functionality. This approach addresses the functional verification of the AMBA AHB to APB Bridge protocol with a focus on completeness. We employ a layered testbench architecture in System Verilog to ensure thorough verification of functionality with maximal coverage. Our verification environment is constructed using System Verilog, and simulations are conducted on the EDA playground platform. Through this comprehensive approach, we aim to provide robust validation of the AHB to APB bridge protocol, ensuring its reliability and compatibility within complex SoC designs. Keywords— Advanced Peripheral Bus (APB), System-On-Chip (SOC), Advanced Microcontroller Bus Architecture.

Longevity of a Brain–Computer Interface for Amyotrophic Lateral Sclerosis

SummaryThe durability of communication with the use of brain–computer interfaces in persons with progressive neurodegenerative disease has not been extensively examined. We report on 7 years of independent at-home use of an implanted brain–computer interface for communication by a person with advanced amyotrophic lateral sclerosis (ALS), the inception of which was reported in 2016. The frequency of at-home use increased over time to compensate for gradual loss of control of an eye-gaze–tracking device, followed by a progressive decrease in use starting 6 years after implantation. At-home use ended when control of the brain–computer interface became unreliable. No signs of technical malfunction were found. Instead, the amplitude of neural signals declined, and computed tomographic imaging revealed progressive atrophy, which suggested that ALS-related neurodegeneration ultimately rendered the brain–computer interface ineffective after years of successful use, although alternative explanations are plausible. (Funded by the National Institute on Deafness and Other Communication Disorders and others; ClinicalTrials.gov number, NCT02224469.)

Exploring human-nature relationships in academic literature on the nitrogen cycle

ABSTRACT The nitrogen (N) cycle is a familiar concept. As is the much simplified, often diagrammatic, representation commonly used to illustrate the scale, importance and interconnectedness of this global cycle that links air, water, rocks and living beings. However, in this representation, humans are often presented as a seemingly minor entity or not explicitly shown at all. This can obscure the idea that humanity is both a direct beneficiary of the nitrogen cycle (through food and resources) and an increasingly significant influence on its function. This study sought to understand how diverse Human-Nature relationships (HNR) are expressed in recent academic literature on the nitrogen cycle. A sample of peer-reviewed literature, containing explicit and inferred examples of HNR and the nitrogen cycle, was analysed using two approaches: 1) network analysis, identifying and illustrating all quantifiable links made between components of the nitrogen cycle, and 2) content analysis to understand how different kinds of terminology were being used to describe relationships between components in the cycle. The network analysis revealed diverse links between ‘human’ and ‘non-human nature’. The content analysis found some explicit use of relational terms, most commonly ‘depend*’. Both approaches highlighted strongly reciprocal links within the ‘human’ realm and the explicit centrality in which this is held across the corpus. We demonstrate the utility of combining quantitative and qualitative analysis to understand nuanced relationships in the nitrogen cycle and explore the utility this has to increase the acknowledgement and appreciation of HNR in science communication and science-policy interface work.

Design of an Embedded Test Bench for Organic Photovoltaic Module Testing

In this article, a multipurpose embedded system for testing organic photovoltaic modules is presented. It is designed to include all the features for real-time monitoring, data acquisition, and power conversion based on a Ćuk converter, providing useful data for scientific investigation of the outdoor operation of organic photovoltaic modules. The embedded system allows both the scan of the I–V curve and the continuous operation of the organic photovoltaic module, such as at its maximum power. Voltage and current at the terminals of the organic photovoltaic module under test and up to four temperatures are continuously measured and stored on a Secure Digital card. The communication interface allows the embedded system to connect with other instruments, such as irradiance sensors, with digital serial output. The embedded system is designed both for laboratory and in-the-field use: it can be powered either by the AC electrical grid or a battery, which can also operate as a backup battery. Galvanic isolation divides the embedded system into the field-side and the logic-side functional sections, providing improved noise immunity and safe operation. The main power distribution system within the embedded system is a +9 V bus; ultra-low-noise linear low dropout regulators provide the +3.3 V and +5 V regulated voltages to supply the analog and digital circuits within the logic-side section, and a flyback converter supplies the field-side section of the board. The proposed embedded solution is validated using an experimental setup built at SolarTechLab, Politecnico di Milano. The experimental results report the feasibility of the proposed embedded system.

CPOpt: A modular framework for genetic algorithm optimization and post-optimization analysis in complex charged particle optical design

This article reports on the development of an optimization framework for charged particle optics design (CPOpt). The optimization part of CPOpt involves a custom-developed Python multi-objective genetic algorithm (MOGA), which incorporates NSGA-II to optimize for multiple objectives, such as particle transmission and beam spot size. The simultaneous tuning of different types of parameters, such as electrode voltages and geometrical parameters, is facilitated by creating isolated groups of parameters. Modeling of parameter configurations is done with the charged particle optics simulation tool SIMION and a ZeroMQ-based communication interface enables a fully automated interaction with the MOGA. The post-optimization analysis part of CPOpt provides standardized and broadly applicable methods to identify suitable solutions, based on the outcome of the optimization part. Global sensitivity analysis, based on the Delta Moment-Independent-Measure in combination with dedicated Latin hypercube sampling, allows higher-level information about parameter sensitivity and robustness to be extracted, as well as effective randomized local optimization. Demonstrated on a two-lens system with intermediate aperture, the CPOpt framework effectively optimized the two conflicting objectives of reduced beam spot size and increased transmission at the detector plane for 12 parameters, covering both electrode voltages and geometrical parameters. The optimization process was performed within less than 11h on a workstation, while all the simulations required for the post-optimization analysis took another 7h. The additional computational effort for the post-optimization analysis can contribute to deliver solutions with high performance and stability.

Design and implementation of a mechatronic system for monitoring worker exposure in cold storage facilities

In response to the increasing need for enhanced occupational safety in cold storage facilities, this study presents the design and validation of a mechatronic time control device specifically developed for monitoring the exposure times of warehouse operators in a multinational company. Over the past two decades, Ecuador has significantly increased regulations to safeguard worker health and safety. In compliance with these regulations, this research addresses the challenges operators face when exposed to sub-zero temperatures during their work shifts. The proposed system integrates mechanical, electronic, and control components to systematically track and manage operators' time within cold rooms, ensuring compliance with predefined safety thresholds. A NodeMCU microcontroller, digital temperature sensors, and a robust communication interface form the device's core. This device records entry and exit times, monitors ambient conditions, and triggers alerts when exposure limits are approached. Extensive validation was conducted using a 3D-printed resin prototype, demonstrating the device's capability to function effectively in harsh environments. The system's efficacy was evaluated through real-world testing, where operators used the prototype during their shifts. Data collected confirmed the device's reliability in tracking exposure times and enhancing worker safety.

An FPGA-Based signal acquisition system for 3D holographic azimuthal electromagnetic resistivity logging instruments

Abstract A signal acquisition system of a 3D holographic azimuthal electromagnetic resistivity logging instrument while drilling is designed based on the Field Programmable Gate Array (FPGA). The azimuth electromagnetic wave resistivity logging instrument is mainly composed of transmitting coils, receiving coils, and control circuits. The signal acquisition system mainly includes the receiving coil and corresponding signal acquisition and processing circuit. First of all, the whole structure of the electromagnetic wave resistivity instrument system while drilling is briefly introduced, and then each function module of the acquisition board is elaborated in detail, and the hardware realization of the signal acquisition module and the corresponding FPGA program design flow chart are given. The acquisition system makes full use of the structured design of the module and First input First output (FIFO) cache technology and can complete the functions of signal acquisition, data transmission, and control on the acquisition board in real-time by using Serial Communication Interface (SCI) information transmission interface. The simulation results show that the system can realize the function of data acquisition and processing well.

Expanding hardware accelerator system design space exploration with gem5-SALAMv2

With the prevalence of hardware accelerators as an integral part of the modern systems on chip (SoCs), the ability to model accelerators quickly and accurately within the system in which it operates is critical. This paper presents gem5-SALAMv2 as a novel system architecture for LLVM-based modeling and simulation of custom hardware accelerators integrated into the gem5 framework. It overcomes the inherent limitations of state-of-the-art trace-based pre-register-transfer level (RTL) simulators by offering a truly “execute-in-execute” LLVM-based model. It enables scalable modeling of multiple dynamically interacting accelerators with full-system simulation support. To create long-term sustainable expansion compatible with the gem5 system framework, gem5-SALAM offers a general-purpose and modular communication interface and memory hierarchy integrated into the gem5 ecosystem, streamlining designing and modeling accelerators for new and emerging applications. gem5-SALAMv2 expands upon the framework established in gem5-SALAMv1 with improved LLVM-based elaboration and simulation, improved and more extensible system integration, and new automations to simplify rapid prototyping and design space exploration. 11Conference Paper Extension: This work extends the work presented in gem5-SALAM: A System Architecture for LLVM-based Accelerator Modeling from MICRO 2020 (Rogers et al., 2020). This work expands on the aforementioned work by revamping the gem5-SALAM internals to provide more robust and extensible simulations, introducing new automation tools for expanding and simplifying design space exploration, and demonstrates the new capabilities of gem5-SALAMv2 by exploring multiple configurations of simple neural network architectures.Validation on the MachSuite (Reagen et al., 2014) benchmarks presents a timing estimation error of less than 1% against the Vivado High-Level Synthesis (HLS) tool. Results also show less than a 4% area and power estimation error against Synopsys Design Compiler. Additionally, system validation against implementations on an Ultrascale+ ZCU102 shows an average end-to-end timing error of less than 2%. Lastly, we demonstrate the upgraded capabilities of gem5-SALAMv2 by exploring accelerator platforms for two deep neural networks, LeNet5 and MobileNetv2. In these explorations, we demonstrate how gem5-SALAMv2 can simulate such systems and guide architectural optimizations for these types of accelerator-rich architectures. 22The most up-to-date version of gem5-SALAMv2 is available at https://github.com/TeCSAR-UNCC/gem5-SALAM..

Unveiling the core of IoT: comprehensive review on data security challenges and mitigation strategies

The Internet of Things (IoT) is a collection of devices such as sensors for collecting data, actuators that perform mechanical actions on the sensor's collected data, and gateways used as an interface for effective communication with the external world. The IoT has been successfully applied to various fields, from small households to large industries. The IoT environment consists of heterogeneous networks and billions of devices increasing daily, making the system more complex and this need for privacy and security of IoT devices become a major concern. The critical components of IoT are device identification, a large number of sensors, hardware operating systems, and IoT semantics and services. The layers of a core IoT application are presented in this paper with the protocols used in each layer. The security challenges at various IoT layers are unveiled in this review paper along with the existing mitigation strategies such as machine learning, deep learning, lightweight encryption techniques, and Intrusion Detection Systems (IDS) to overcome these security challenges and future scope. It has been concluded after doing an intensive review that Spoofing and Distributed Denial of Service (DDoS) attacks are two of the most common attacks in IoT applications. While spoofing tricks systems by impersonating devices, DDoS attacks flood IoT systems with traffic. IoT security is also compromised by other attacks, such as botnet attacks, man-in-middle attacks etc. which call for strong defenses including IDS framework, deep neural networks, and multifactor authentication system.

MOBILE ROBOT TRACKING SYSTEM BASED ON MACHINE VISION AND LASER RADAR

The proposed solution addresses the issue of insufficient real-time performance and accuracy in mobile robot path tracking by introducing a system that combines machine vision and laser radar. In this study, the Broadcom BCM2711 microcontroller chip is connected to the RS232 communication interface for transmitting information to the ARM embedded processor. Users can access position distance, direction, and other robot-related data through the man-machine interface's LCD display in a Windows operating system environment. By initiating an adaptive position tracking algorithm program identified by the robot within the position tracking unit, mobile position tracking of the robot is achieved. Experimental results demonstrate significant improvements in both real-time performance and accuracy of this mobile robot tracking system.

Effectiveness and mechanism of Huoxin pill on heart failure after percutaneous coronary intervention: Study protocol for a double-blind, randomised, placebo-controlled parallel trial

BackgroundCoronary heart disease (CHD) is the most common cardiovascular disease facing human beings. Cardiac remodelling is an important pathological factor for the progression of heart failure (HF) after CHD. At present, Chinese medicine is widely used in the treatment of HF, but there are still some drugs lack of evidence-based and mechanism evidence. Multi-omics techniques can deep explore candidate pathogenic factors and construct gene regulatory networks.This trial is intended to evaluate the effect on Huoxin pill (HXP) in the treatment of HF after programmable communication interface (PCI). Meantime, multi-omics analysis technique will be used to target the fundamental pathological links of cardiac remodelling, so as to study the mechanism of HXP in the treatment of HF after PCI. MethodsThis study is a randomized, double-blind, placebo-controlled trial. Sixty patients with HF undergoing PCI are recruited from the First Affiliated Hospital of Henan University of CM. All selected patients will be randomly attributed to receive conventional treatment + HXP or placebo. The packaging, dosage and smell of placebo and heart activating pill were identical. The primary outcome is NYHA cardiac function grade, while the secondary outcomes included Lee's HF score, exercise tolerance test, and quality of life evaluation. Additional indicators include cardiac ultrasound, electrocardiogram, 24-h dynamic electrocardiogram, myocardial injury indicators, and energy metabolism indicators. DiscussionThis study may provide a new treatment option for patients with HF after PCI and provide evidence for the treatment of CHD and HF with HXP. Trial registration2023-10-08 registered in China Clinical Trial Registry, registration number ChiCTR2300076402.